Citable — AI-visibility check

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and openWorldHint annotations, the description discloses the paid nature with exact pricing, the output shape (mentioned, position, cited-domain list), per-engine execution, run-to-run variability, and the no-charge condition. This gives the agent an unusually complete picture of the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact but information-dense, front-loading cost and then moving progressively through behavior, output, and repeat-call guidance. Every sentence contributes necessary operational detail with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even without an output schema, the description defines the return fields well enough for an agent to anticipate results. It covers cost, engine scope, citation mechanics, variability, and a charging edge case, making the tool callable with minimal ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents prompt, domain, and engines. The main description adds cross-cutting context about engines and pricing but does not materially extend the parameter-level semantics beyond what the schema provides. A baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('asks the AI answer engines... and reports which ones cite the domain'), a concrete resource (AI engines, domain), and clarifies through context that this is an AI visibility check. It clearly differentiates from sibling tools by focusing on live engine citations rather than reports or keyword data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear context for when to use the tool: checking whether AI engines cite a domain. It also adds practical guidance on calling 2–3 times because answers vary between runs. It does not explicitly contrast with alternatives like citable_citability_report or citable_ai_share_of_voice, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.